The present invention relates generally to an ultrasound diagnostic system, and more particularly, to an ultrasonic apparatus and method for automatically measuring the velocities of tissues within the human body by using the Doppler effect.
Ultrasound diagnostic systems using the Doppler effect are well known in the art and typically used for detection of the velocities of blood flows and tissues within the human body. These conventional ultrasound diagnostic systems determine the velocity of a target object, such as a red blood cell, by detecting a frequency or phase shift of echo signals, due to movement of the target object, which have been reflected from the target object based on transmitted ultrasound signals.
Referring to FIG. 1, the principle of measuring the velocity of blood flow and tissue by using ultrasound signals is explained. Transducer array 103 transmits ultrasound signals toward target object 101, and repeats sampling operations upon the echo signals reflected from target object 101, several times, e.g., 2N times. FIG. 1 exemplifies sampling done at the timing, t=t0. As the target object moves, the phases of the signals sampled at the timing, t=t0 change. From the degree of the phase changes, the velocity of target object 101, xcexd, may be calculated according to Equation 1 below:                     v        =                                            Δ              Θ                        ⁢                          λ              0                                            2            ⁢            π            ⁢                          xe2x80x83                        ⁢                          T              PRF                                                          (                  Eq          .                      xe2x80x83                    ⁢          1                )            
where TPRF is an interval at which ultrasound signals are transmitted, i.e., the reciprocal of a pulse repetition frequency (PRF), xcex0 is a center frequency of the ultrasound signals being transmitted, and xcex94"THgr" is a phase change.
As can be seen from Equation 1, the velocity of the target object is proportional to the phase change of the echo signals reflected from the target object. Since the frequency shift of the signal is proportional to the phase change, the velocity of the target object, xcexd, is proportional to the frequency shift of the reflected echo signal. Therefore, measuring the frequency of the echo signals reflected from the target object provides the velocity of the target object.
Referring to FIG. 2, which shows a block diagram of a conventional ultrasound diagnostic apparatus for measuring the velocity of blood flow and human tissue, ultrasound diagnostic apparatus 200 comprises transducer array 103, pre-amplifier 104, time gain control (TGC) amplifier 105, analog-to-digital (A/D) converter 106, quadrature demodulator 107, digital signal processor 108, and display 109.
Transducer array 103 transmits ultrasound signals toward the target object and receives echo signals reflected from the target object. The echo signals are amplified by pre-amplifier 104. TGC amplifier 105 amplifies the pre-amplified signals from pre-amplifier 104 while varying gain to compensate for attenuation of the ultrasound signals as they propagate inside the human body. A/D converter 106 converts an output signal of TGC amplifier 105 from analog to digital and quadrature demodulator 107 demodulates the signal to be inputted to digital signal processor 108. Digital signal processor 108 detects the velocity of the target object based on 2N number of sampled data, which are obtained by repeating transmission of an ultrasound signal toward the target object, 2N times, and transmits the detected velocity to display 109.
The ultrasound signals transmitted by transducer array 103 are reflected from blood, tissues, muscles, and the like within the human body. In the case of blood, the ultrasound signals are reflected from a plurality of red blood cells, each of which has a different velocity. Since the sampled data being inputted to digital signal processor 108 contain a plurality of velocity components, digital signal processor 108 computes a velocity distribution spectrum of the sampled data and transmits the same to display 109. Display 109 then displays the velocity distribution spectrum of the sampled data thereon.
Referring to FIG. 3, which shows a block diagram of digital signal processor 108 shown in FIG. 2, digital signal processor 108 comprises clutter filtering part 301, fast Fourier transform (FFT) part 302, and post-processing part 303. Where ultrasound diagnostic apparatus 200 is used for measuring the velocity of blood flow, clutter filtering part 301 cuts off echo signals (so called clutters) reflected from tissues and/or muscles within the human body. These echo signals have low-band frequencies, since movement of tissue and muscle is slower than that of blood within the human body. Thus, clutter filtering part 301 employs a high-pass filter for computing velocity of blood flow.
If ultrasound diagnostic apparatus 200 is used for measuring the velocity of tissue within the human body, clutter filtering part 301 cuts off echo signals reflected from blood. In order to compute the velocity component of tissue, clutter filtering part 301 employs a low-pass filter instead of the high-pass filter to cut off the velocity components of blood flow.
FFT part 302 performs a Fourier transform on the 2N number of sampled data to create frequency distribution data containing 2N number of frequency components. This frequency distribution data corresponds to the velocity distribution data of the target object. Post-processing part 303 performs known signal processing on the frequency distribution data, such as log compression and base line shifting, in order to obtain improved image quality. The frequency distribution data, i.e., the velocity distribution data of the target object, outputted from digital signal processor 108, is displayed on display 109.
Referring to FIG. 4, which shows a graph of typical frequency distribution data, the X-axis represents frequency components and Y-axis represents the strength of the frequency components. The frequency distribution data may represent the strength of the frequency components or, alternatively, some other value, such as the square of the strength. A positive frequency and a negative frequency represent signal components reflected from target objects that move in opposite direction. That is, xe2x80x9cpositivexe2x80x9d and xe2x80x9cnegativexe2x80x9d denote relative direction of movement. As can be seen from FIG. 4, the strength of the negative frequency component tends to be larger than that of the positive frequency component. This means that the blood flows in a certain direction, such as away from transducer array 130.
Referring to FIGS. 5 and 6, employing a low-pass filter to cut off the velocity component of blood flow in order to measure the velocity component of tissue within the human body has some drawbacks. Calculating a cut-off frequency to precisely discriminate the velocity component of tissue from that of blood flow within the human body is very difficult. Changing the calculated cut-off frequency whenever the velocity of tissue is varied is also very difficult.
FIG. 5 shows a diagram of a conventional low-pass filtering scheme for isolating the velocity component of tissue within the human body. FIG. 6 shows a diagram of a method for designing a cut-off frequency that discriminates the velocity component of tissue from that of blood flow by using a conventional low-pass filtering scheme in a conventional ultrasound diagnostic apparatus.
Referring to FIG. 5, in a conventional ultrasound diagnostic apparatus, a low-pass filter 703 is designed on the basis of maximum frequency 701-1 in the frequency band representative of a velocity component of tissue 701, which appears in a low frequency band, in order to isolate the velocity component of tissue 701. Determining a cut-off frequency 704 for precisely discriminating the velocity component of tissue 701 from that of blood flow 702 is very important. However, the low-pass filtering scheme shown in FIG. 5 is difficult to adapt to an ultrasound diagnostic apparatus. Therefore, in a conventional ultrasound diagnostic apparatus, a low-pass filter designed as shown in FIG. 6 may be employed.
If the velocity component of tissue is limited to a predetermined velocity range, designing low-pass filter 703 on the basis of maximum frequency 701-1 of the velocity component of tissue 701 may be possible as shown in FIG. 5. However, since the velocity component of tissue 701 is actually different for each target object to be measured, determining a fixed cut-off frequency is very difficult.
As shown in FIG. 6, where the velocity component of tissue 701 is mixed with the velocity component of blood flow 702 having a low frequency component, designing a filter 703-1 with a low cut-off frequency results in the decrease in the velocity component of tissue 701, by as much as portion 701-2, while designing a filter 703-1 with a high cut-off frequency results in the high cut-off frequency containing the velocity component of blood flow 702. Thus, determining a cut-off frequency 704 for discriminating the velocity component of tissue 701 from the velocity component of blood flow 702 is very difficult in designing a filter.
Another drawback is that the velocity component of tissue within the human body may be erroneously calculated due to aliasing when a digital signal is processed. Referring to FIG. 7, the velocity component of tissue appears in a low frequency domain and the velocity component of blood flow appears in a high frequency domain. However, if the sampling frequency does not have a sufficiently high frequency, aliasing occurs such that the velocity component of blood flow 702 appears in the frequency domain of the velocity component of tissue 701. That is, where the velocity component of blood flow 702 appears within the velocity component of tissue 701 due to aliasing as shown in FIG. 7, the velocity component of tissue 701 will appear greater than its actual value. Thus, frequencies of the velocity component and power component are distorted whenever the velocity component of blood flow 702 is varied. This results in decreased reliability of the measured data.
Yet another drawback is that designing a filter with a cut-off frequency for discriminating the velocity component of tissue from that of blood flow by means of a finite-impulse-response (FIR) filter with a limited filter order is very difficult. Although designing a filter having a desired cut-off frequency by increasing the filter order is possible, delays corresponding to (the filter order (N)xe2x88x921)/2 degrade the real-time processing capability. Also, in a gap filling mode, data sections (number of gaps+order of filter (N)xe2x88x921) have to be filled, as will be described in detail with reference to FIGS. 8 to 12.
FIG. 8 shows a timing sequence in a typical brightness/Doppler (B/D) simultaneous mode. FIG. 9 shows a timing sequence in a gap filling mode. FIGS. 10A and 10B show views explaining the principle of spectrum gap filling. Here, B and D modes are used for obtaining a tomograph image and Doppler data, respectively. The B/D simultaneous mode is used for obtaining both a tomograph image and Doppler data.
In B/D simultaneous mode of a conventional ultrasound diagnostic apparatus employing a timing sequence shown in FIG. 8, raising a Doppler PRF to a sufficient level is difficult. For example, where blood flow within the heart is observed in a pulsed-wave (PW) Doppler simultaneous mode, aliasing greatly affects the Doppler spectrum so that analyzing the Doppler spectrum may be very difficult.
However, raising the Doppler PRF by two times is possible by implementing PW Doppler simultaneous mode with the timing sequence shown in FIG. 9 and approximately reconstructing the time gap in the PW Doppler simultaneous mode with image/audio artifacts from previous and next Doppler signals. In FIG. 9, a time interval required to obtain the B mode is associated with a minimum B mode frame rate that is synchronized with the PRF. Thus, the time interval acts as a time gap so that filling the time gap may increase the reliability of measured data.
Referring to FIGS. 10A and 10B, which show views explaining the principle of spectrum gap filling, in a conventional ultrasound diagnostic apparatus, a time gap, between t1 to t2, is filled by using linear interpolation.
Referring to FIG. 11, the number of data intervals, as much as (number of gaps+order of the filter (N)xe2x88x921), must be filled. For example, where the number of gaps is 4 and the order of filter is 5, the number of filtered data is 8. This means that actually 8 gaps have to be filled despite the number of gap intervals being 4. If data in the gap interval is distorted data or zero, the filtered data may be distorted. Also, as the filter order is increased, the number of gaps to be filled is increased, so that discriminating the velocity component of tissue from the velocity component of blood flow is difficult. As a result, increasing the filter order is practically limited.
As will be described in detail with reference to FIG. 12, where the filter order is increased under such limitation, delays, (order of filter (N)xe2x88x921)/2), occur so that real-time processing capability may be degraded. As shown in FIG. 12, if the filter order is 9, filtered data 1 can be outputted when data 1 to data 9 are inputted. In such a case, if the order of the filter is increased, the delay is increased as mentioned above. Therefore, the delay interval is increased as the filter order is increased so that real-time processing capability may be degraded.
Due to the afore-mentioned drawbacks, a conventional ultrasound diagnostic apparatus cannot effectively measure the velocity component of tissue within the human body by using a low-pass filter, which results in decreased reliability of the measured data.
Therefore, one objective of the present invention is to provide an ultrasound diagnostic apparatus and method for effectively measuring the velocity of tissue within the human body by using the Doppler effect.
Another objective is to provide an ultrasound diagnostic apparatus and method for measuring the velocity of tissue within the human body in real-time without using a low-pass filter.
Yet another objective is to provide an ultrasound diagnostic apparatus and method for effectively eliminating the velocity component of blood flow without using a low-pass filter, to thereby reliably measure the velocity of tissue within the human body.
In accordance with one aspect of the present invention, an ultrasound diagnostic apparatus is provided for measuring a velocity component of tissue and blood flow within a human body, comprising: a sample data generator for generating sample data by transmitting ultrasound signals to and sampling echo signals reflected from the human body; generating means for generating frequency distribution data containing the velocity component of tissue and blood flow by processing the sample data, wherein the frequency distribution data contains a plurality of frequency components, each of which has a power level; detecting means for extracting the frequency distribution data corresponding to the velocity component of tissue flow from the frequency distribution data, by using a maximum value of the velocity component of blood flow; and a display coupled to the detecting means for displaying the extracted frequency distribution data.
In accordance with another aspect of the present invention, a method is provided for measuring a velocity component of tissue and blood flow within a human body, comprising the steps of: generating sample data by transmitting ultrasound signals to and sampling echo signals reflected from the human body; generating frequency distribution data containing the velocity component of tissue and blood flow by processing the sample data, wherein the frequency distribution data contains a plurality of frequency components, each of which has a power level; extracting the frequency distribution data corresponding to the velocity component of tissue flow from the frequency distribution data, by using a maximum value of the velocity component of blood flow; and displaying the extracted frequency distribution data.